Context-Aware Building Model Search for Maintenance Records
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Solution Overview
Problem
Traditional hard-copy documentation in the construction industry is inefficient and prone to missing relevant information due to incomplete records, different document versions, and the inability to understand certain document types, making it difficult to answer questions about a building's history and maintenance needs.
Innovation Solution
A digital building portfolio system incorporating a context-aware search engine that utilizes machine learning and artificial intelligence to process building plans and documents, generating vector embeddings for efficient multi-modal searching and providing conversational responses to user queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional hard-copy documentation is used to store building information, then information can be retained for the lifetime of the structure, but it becomes inefficient and prone to missing relevant information due to incomplete records, different document versions, and inability to understand certain document types
Solution Approach 1:
The patent creates a digital copy (3D model) of the building that replicates and integrates information from multiple hard-copy documentation sources. This digital model serves as a unified representation that consolidates blueprint data, maintenance records, and other building information into a single searchable format, eliminating version control issues and improving both reliability and retrieval efficiency
Solution Approach 2:
The system introduces an intermediary processing layer that includes image recognition algorithms and natural language processing capabilities. This intermediary automatically extracts and structures information from various document types (including images and handwritten notes), converting unstructured hard-copy data into structured digital information that can be efficiently queried and cross-referenced
2Loss of information
If multiple document versions and types are maintained to ensure comprehensive building information, then information completeness improves, but difficulty in understanding and retrieving relevant information increases
Solution Approach 1:
The patent segments building information into distinct categories (structural elements, electrical systems, plumbing, maintenance history, etc.) and organizes them as separate searchable attributes within the 3D model. This segmentation allows users to query specific information types without being overwhelmed by the entire dataset, reducing retrieval difficulty while maintaining information completeness
Solution Approach 2:
The 3D model serves as a universal platform that can store, display, and search multiple types of building information simultaneously. It functions as both a visual representation of the building structure and a database for maintenance records, blueprint data, and operational information, eliminating the need to switch between different document formats and versions
3Loss of information
If detailed building documentation is maintained to facilitate future maintenance and renovations, then information completeness improves, but time required to review and understand documents increases
Solution Approach 1:
The system performs preliminary processing of building documentation during the digitization phase, automatically extracting key information, categorizing it by building component, and pre-tagging with relevant metadata. This preliminary action ensures that when maintenance or renovation needs arise, the information is already organized and ready for rapid retrieval without requiring time-consuming manual review
Solution Approach 2:
The patent replaces the mechanical process of manual document review with automated digital search and image recognition systems. Users can query the 3D model using natural language or by selecting visual elements, and the system automatically retrieves relevant maintenance records and building information, eliminating the time required to manually search through physical or digital document stacks
Data Source
AI summary
A search engine for providing intelligent or conversational responses to user queries into a digital building portfolio are disclosed. In embodiments, a search engine receives a user query and query context. The query and query context are processed and used to search into a vector database and knowledge graph database that are generated from data in the digital building portfolio. The results of the search are used to retrieve relevant data from the digital building portfolio, which are then summarized and used to generate an appropriate response. Other embodiments may be described and/or claimed.